Monumental Papers in Kalman & Particle Filtering

Kalman Filter Foundations

Kalman, R.E. (1960) – A New Approach to Linear Filtering and Prediction Problems, J. Basic Eng.

Kalman, R.E. & Bucy, R.S. (1961) – New Results in Linear Filtering and Prediction Theory, J. Basic Eng.

Rauch, H.E., Tung, F., & Striebel, C.T. (1965) – Maximum Likelihood Estimates of Linear Dynamic Systems, AIAA J.

Schmidt, S.F. (1966) – Application of State-Space Methods to Navigation Problems

Singer, R.A. (1970) – Estimating Optimal Tracking Filter Performance for Manned Maneuvering Targets, IEEE TAC

Bar-Shalom, Y. & Tse, E. (1975) – Tracking in a Cluttered Environment with Probabilistic Data Association, Automatica

Blackman, S.S. (1986) – Multiple-Target Tracking with Radar Applications (book)

Blom, H.A.P. & Bar-Shalom, Y. (1988) – The Interacting Multiple Model Algorithm, IEEE TAC

Bar-Shalom, Y. & Fortmann, T. (1988) – Tracking and Data Association (book)

Blair, W.D. (1990s) – Papers on IMM filtering for maneuvering radar targets

Gelb, A. (ed.) (1974) – Applied Optimal Estimation

Maybeck, P.S. (1979) – Stochastic Models, Estimation, and Control

Brown, R.G. & Hwang, P.Y.C. (1996) – Introduction to Random Signals and Applied Kalman Filtering

Titterton, D.H. & Weston, J.L. (1997/2004) – Strapdown Inertial Navigation Technology

Grewal, M.S. & Andrews, A.P. (1993–2015 editions) – Kalman Filtering: Theory and Practice Using MATLAB

Gordon, N.J., Salmond, D.J., & Smith, A.F.M. (1993) – Novel Approach to Nonlinear/Non-Gaussian Bayesian State Estimation

Isard, M. & Blake, A. (1998) – CONDENSATION – Conditional Density Propagation for Visual Tracking, IJCV

Doucet, A., Godsill, S., & Andrieu, C. (2000) – On Sequential Monte Carlo Sampling Methods for Bayesian Filtering

Doucet, A., de Freitas, N., & Gordon, N. (eds.) (2001) – Sequential Monte Carlo Methods in Practice

Del Moral, P. (2004) – Feynman–Kac Formulae: Genealogical and Interacting Particle Systems with Applications

Evensen, G. (1994) – Sequential Data Assimilation with a Nonlinear Quasi-Geostrophic Model Using Monte Carlo Methods, J. Geophys. Res.

Julier, S.J. & Uhlmann, J.K. (1997) – A New Extension of the Kalman Filter to Nonlinear Systems, Proc. SPIE

Wan, E.A. & van der Merwe, R. (2000) – The Unscented Kalman Filter for Nonlinear Estimation

van der Merwe, R. & Wan, E.A. (2003) – Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models

Arasaratnam, I. & Haykin, S. (2009) – Cubature Kalman Filters, IEEE TAC